SIMULATION AND PROBABILISTIC MODELING

Name: SIMULATION AND PROBABILISTIC MODELING
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Rating: 4.3 (1632 reviews)

ISYE 320

과목 설명

Analysis of stochastic systems using both analytic methods and computer simulation. Empirical and theoretical models of arrival and service processes. State spaces and state transition probabilities. Simulation of queuing and manufacturing systems. Continuous time Markov analysis of manufacturing systems. Simulation project management, testing and emerging trends.

선수과목

(MATH/STAT 309 , STAT 311 , MATH/STAT 431 , MATH 531 or concurrent enrollment) and (ISYE 210 , ECE 331 , MATH/STAT 310 , STAT 312 , STAT 324 , STAT 371 , or concurrent enrollment) and (MATH 320 , MATH 340 , or concurrent enrollment), or member of Engineering Guest Students

충족 요건

ISYE 417 , ISYE 615 , ISYE 450 , and ISYE 321

학점

미보고

개설 시기

미보고

평점

3.45

0.06% 과거 데이터 대비

수료율

97.37%

-1.85% 과거 데이터 대비

A 비율

23.68%

-41.88% 과거 데이터 대비

학급 규모

-13.85% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

다음 사이트의 평점순으로 정렬 Rate My Professors

유사 과목

SIMULATION MODELING LABORATORY

ISYE 321

Computer exercises involving generation and analysis of random variables, spreadsheet models of queuing systems, use of simulation software packages. Project.

SIMULATION MODELING AND ANALYSIS

ISYE 620

Introduction to simulation modeling and analysis techniques with application to production, logistics, service, and other systems. Emphasis on model building, application of basic statistical data analysis, and the use of simulation for design, evaluation, and improvement of such systems. Introduction to available software. Case studies.

INTRODUCTION TO STOCHASTIC PROCESSES

ISYE/MATH/OTM/STAT 632

Topics include discrete-time Markov chains, Poisson point processes, continuous-time Markov chains, and renewal processes. Applications to queueing, branching, and other models in science, engineering and business.

PERFORMANCE ANALYSIS OF MANUFACTURING SYSTEMS

ISYE/ME 643

Examines the state of the art in the use of stochastic network theory to develop performance models of modern manufacturing systems.

STOCHASTIC MODELING TECHNIQUES

ISYE 624

Techniques for modeling systems in which uncertainty is an essential factor. Emphasizes why, how and when techniques can or cannot be applied, rather than their mathematical derivation. Case studies and/or examples from such areas as logistics, production, and service industries.